Preventing transition “regret”: An institutional ethnography of gender-affirming medical care assessment practices in Canada
Bibliographic record
Abstract
When a person openly "regrets" their gender transition or "detransitions" this bolsters within the medical community an impression that transgender and non-binary (trans) people require close scrutiny when seeking hormonal and surgical interventions. Despite the low prevalence of "regretful" patient experiences, and scant empirical research on "detransition", these rare transition outcomes profoundly organize the gender-affirming medical care enterprise. Informed by the tenets of institutional ethnography, we examined routine gender-affirming care clinical assessment practices in Canada. Between 2017 and 2018, we interviewed 11 clinicians, 2 administrators, and 9 trans patients (total n = 22), and reviewed 14 healthcare documents pertinent to gender-affirming care in Canada. Through our analysis, we uncovered pervasive regret prevention techniques, including requirements that trans patients undergo extensive psychosocial evaluations prior to transitioning. Clinicians leveraged psychiatric diagnoses as a proxy to predict transition regret, and in some cases delayed or denied medical treatments. We identified cases of patient dissatisfaction with surgical results, and a person who detransitioned. These accounts decouple transition regret and detransition, and no participants endorsed stricter clinical assessments. We traced the clinical work of preventing regret to cisnormativity and transnormativity in medicine which together construct regret as "life-ending", and in turn drives clinicians to apply strategies to mitigate the perceived risk of malpractice legal action when treating trans people, specifically. Yet, attempts to prevent these outcomes contrast with the material healthcare needs of trans people. We conclude that regret and detransitioning are unpredictable and unavoidable clinical phenomena, rarely appearing in "life-ending" forms. Critical research into the experiences of people who detransition is necessary to bolster comprehensive gender-affirming care that recognizes dynamic transition trajectories, and which can address clinicians' fears of legal action-cisgender anxieties projected onto trans patients who are seeking medical care.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.023 | 0.014 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".